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Cancer Epidemiology Biomarkers & Prevention Vol. 15, 25-31, January 2006
© 2006 American Association for Cancer Research

Unlimited Access to Care: Effect on Racial Disparity and Prognostic Factors in Lung Cancer

Charles R. Mulligan1, Amir D. Meram4,3, Courtney D. Proctor4, Hongyu Wu3, Kangmin Zhu3 and Aizen J. Marrogi4,2

Divisions of 1 Cardiothoracic Surgery and 2 Anatomic Pathology; 3 Departments of Surgery, Pathology, and Area Laboratory Services and U.S. Military Cancer Institute, Walter Reed Army Medical Center, Washington, District of Columbia; and 4 Laboratory of Biomarkers and Carcinogenesis, CBCP-IRC 2 Department of Surgery, Uniformed Services University for Health Sciences, Bethesda, Maryland

Requests for reprints: Aizen J. Marrogi, Division of Anatomic Pathology, Department of Pathology and Area Laboratory Services, Walter Reed Army Medical Center, Room #4710A, 6900 Georgia Avenue, Northwest, Washington, DC 20307-5001. Phone: 202-792-5781; Fax: 202-782-3217. E-mail: Aizen.Marrogi{at}na.amedd.army.mil


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Study Objective: Evaluate the prognostic factors influencing lung cancer survival under a universal health care system and determine if access to care eliminates clinical outcome disparity.

Design: Retrospective case series review.

Background: Lung cancer survival is worse in men and in African Americans, thought to be related to poor general health in men and limited access to heath care in African Americans. The Military Health Care System, with unlimited access to care, provides an excellent setting for evaluating gender and racial disparities in lung cancer survival.

Methods: Lung cancers diagnosed at Walter Reed Army Medical Center, from 1990 to 2000, were evaluated by chart review for age, gender, race, smoking history, cancer history, histology, stage, and completeness of resection.

Results: Seven hundred thirteen Caucasians and 173 African Americans, 2:1 male predominance, had a 22% 5-year survival. Cox model analysis showed that male gender [hazard ratio (HR, 1.31) 95% confidence interval (95% CI), 1.02-1.68], advanced-stage disease (stage III: HR, 2.58; 95% CI, 1.57-4.26/stage IV: HR, 4.20; 95% CI, 2.51-7.41), and incomplete resection (HR, 4.06; 95% CI, 2.75-5.99) were predictors of poor outcome; whereas bronchoalveolar carcinoma features (HR, 0.35; 95% CI, 0.23-0.52) and smoking cessation >7 years (HR, 0.70; 95% CI, 0.49-0.99) were predictors of favorable outcome. No ethnic differences in survival were observed.

Conclusions: No racial disparities in survival when access to medical care is universal. Male gender, incomplete resection, and advanced stage are significant predictors of poor outcome in lung cancer. (Cancer Epidemiol Biomarkers Prev 2006;15(1):25–31)


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Lung cancer is the leading cause of cancer death in both men and women in the United States. An expected 174,000 cases of new lung cancer are expected to be diagnosed in 2004 with an estimated 160,000 deaths related to lung cancer. The lung cancer cure rates continue to be an abysmal 5-year survival of 15%. The 1995 to 2000 American Cancer Society survival data for Caucasian patients with lung cancer was 15.4% compared with 13.2% for their African-American counterparts. The best survival outcomes observed are those of Caucasian females with a 5-year survival of 17.4%, and the worst data are among African-American males at 11.9% (1). This poor outcome in survival has been be attributed to multiple variables, including molecular, biological, and physiologic, including disparity in access to health care among different ethnic groups.

Several authors have analyzed survival data in various case series to glean which factors portend a poor outcome. Since 1990, >876 studies reported multivariate analyses that identified 169 prognostic factors relating either to the tumor or the host of lung cancer (2). Notwithstanding stage, gender and race have been suggested as independent prognostic determinants (3) in addition to smoking duration (4) especially in women (5). Across all disease stages, survival for African-American patients continues to lag behind that reported for non–African-American patients (6-8). History of cancer, personal or family, and histologic type may represent factors that may predispose to poorer survival outcome (9-11), suggesting a genetic susceptibility to lung cancer. One variable, which has yet to be completely analyzed, is access to health care, although several studies have linked socioeconomic and location of medical treatment facility to poor outcomes in lung cancer (12-14). Studies linking outcome of several malignancies, including lung to availability of health insurance, have found that purported disparities in cancer outcome may be related to access to quality care, highlighting the significance of early screening (15-17). In the current health care system in the United States, this is quite difficult to analyze, because there is no uniform system and there is a disparity between private payers Medicare and Medicaid.

Military Health Care System offers a unique opportunity to evaluate outcomes of patients with unlimited access to care. Military Health Care System is the largest health care provider in the country that provides premium health care services for U.S. military servicemen and women, their dependents, and retirees. By evaluating the prognostic indicators of cancer survival in this group of patients, we are theoretically able to assess whether there are racial disparities in lung cancer survival when equal medical care is provided, and what other factors may be related to the outcome of this disease. We undertook this study to analyze lung cancer patients' clinical outcomes and to determine if the same access to care changed the noted disparities in survival among various ethnic and gender patient population groups, and what other factors might be associated with lung cancer survival.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
The Walter Reed Army Medical Center Tumor Registry was queried to find all lung cancers diagnosed from 1990 to 2000 (tumor site 340-349). Additionally, the convenience files of the Thoracic Surgery Tumor Clinic were cross-referenced to the registry, and additional patients were added who had not been previously registered. 1,053 patients were identified with lung cancer, of which 907 non–small cell lung cancers (NSCLC) were enrolled in this study. Age, gender, race, smoking history, family/personal history cancer, histology, stage, and completeness of resection were evaluated by chart review. The follow-up period ranged from 1 to 12 years, with 5 years follow-up available on 807 patients (666 dead and 137 alive) and 10-year follow-up available on 724 patients, including 706 dead and 18 live.

Lung cancer patients' survival was analyzed according to race, age, gender, stage, histology, completeness of tumor resection, history of smoking, and history of cancer (personal or family). The analytic outcome was death. The time between the diagnosis of lung cancer and death was calculated. Data were truncated if a patient did not decease at the end of the study period.

In the data analysis, we first estimated the crude survival using the Kaplan-Meier method, in which the survival at 25th, 50th, and 78th percentiles in time was estimated for each level of the study variable, and the log-rank test was used to calculate the significance of the difference between the different levels. No other variables were adjusted in Kaplan-Meier analysis. We then estimated the survival with adjustment for potential confounding factors, using Cox proportional hazard survival model: Hj(t)/H0(t) = e({alpha}t + ß1x1j + ß2x2j + ß3x3j...), where Hj(t) is the hazard function at time t for study subject j and H0(t) is the baseline hazard function at time t. {alpha}t represents the intercept, x1j, x2j, x3j are the values of study variables 1, 2, 3, and ß1, ß2, ß3 are the coefficients for x1j, x2j, x3j. The hazard ratio (HR), Hj(t)/H0(t), which reflects the risk of death relative to the baseline level, and its 95% confidence interval (95% CI) were calculated.

For the Cox proportional hazard model analysis, we first assessed the effect of each factor of interest on survival while adjusting for demographic variables and then included all demographic variables and other variables in the Cox model to control for potentially mutual confounding effects on lung cancer survival. We also examined whether the relationship between a factor and lung cancer survival was modified by racial background or age. This was done by testing the interaction term between a variable and race or family history while controlling for demographic variables.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Patient Characteristics
Nine hundred seven patients were identified to have NSCLC from 1990 to 2000, including 713 Caucasian Americans (79%), 173 African Americans (19%), and 21 other or unspecified nationalities with a 2:1 male-to-female ratio.

The histology of the tumor showed 384 (42%) adenocarcinomas, 280 (31%) squamous cell carcinomas (SCC), 181 (20%) non–small cell not otherwise specified (NSCC-NOS), and 62 (7%) other carcinomas (3% large cell, 3% adenosquamous, and 1% bronchoalveolar carcinoma). Adenocarcinomas occurred more frequently in females (White female, 53.1%; Black female, 51.1%; White male, 41.1%; Black male, 42.1%). SCC was more commonly seen in males especially Caucasians (White male, 38.5%; White female, 29.1%; Black male, 27.2%; Black female, 26.7%). African-American patients were more likely to have a diagnosis of NSCLC-NOS (Black male, 30.7% and Black female, 26.7% versus White male, 20.5%, White female, 17.8%; see Table 1).


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  		Table 1. Distribution of lung cancers based upon age, histology, differentiation, and stage according to race and gender

 
There were 144 stage IA (15.9%), 141 stage IB (15.5%), 16 stage IIA (1.8%), 57 stage IIB (6.3%), 95 stage IIIA (10.5%), 180 stage IIIB (19.8%), and 274 stage IV (30.2%) lung cancers. Racial distribution of stage was similar with the exception slightly higher predominance of stage IV disease in African-American patients, most notably African-American males (see Table 1). The univariate analysis of stage IIA and IIB and stage IIIA and IIIB showed similar survival and were grouped into stage II and stage III, respectively, for data evaluation.

Racial and Gender Comparisons in Lung Cancer Survival
Figure 1 shows the Kaplan-Meier estimates of lung cancer survival by racial background. There is no significant survival differences between races, although the number of patients with other racial background was relatively small (P = 0.298). Table 2 further breaks down the 5-year survival for race and gender and compares them to the national average based upon Surveillance, Epidemiology, and End Results data published by the American Cancer Society for the same period. The 5-year survival rates were 22.7% and 22.3% among Caucasians and African Americans, respectively, whereas the 10-year survival rates were 12.2% and 11.2%, respectively. This racial disparity is not statistically different; however, there were significant gender differences noted in lung cancer survival (Figs. 1 and 2). The 5-year and 10-year survival rates were 19.4% and 10.2% for men, respectively; the corresponding estimates were 28.9% and 15.5% for women, respectively. The difference was statistically significant (P < 0.0001).


Figure 1
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  		Figure 1. Kaplan-Meier survival curve for lung cancer based on race (1990-2000, Walter Reed Army Medical Center).

 

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  		Table 2. WRAMC survival data based upon Kaplan-Meier survival curves compared with published SEER data for year 2000

 

Figure 2
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  		Figure 2. Kaplan-Meier Curve for survival based on race and gender (1990-2000, Walter Reed Army Medical Center).

 
As described above, different racial and gender groups differed in tumor histology, stage, and grade. Descriptive analyses showed that the two comparison groups by race and gender might also be different in age, pack-years of smoking, family or personal history of cancer, tumor size, stage and grade of cancer, histology of cancer, and surgical treatment. To control for the potential effects of these variables on the results by race or gender, Cox model analyses were conducted. The results showed that the HR estimate was 1.0 (95% CI, 0.8-1.2) for African Americans compared with Caucasians after adjustment for age, tumor stage, tumor grade, cancer history, personal and family histories of cancer, surgical treatment, pack-years of smoking, and number of years quit. However, the adjusted HR estimate for gender was 1.4 (95% CI, 1.1-1.6) for men compared with women (see Table 3).


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  		Table 3. Multivariate analysis using Cox regression analysis

 
Other Factors in Relation to Lung Cancer Survival
The Kaplan-Meier estimates were not significant for family (P = 0.443) or personal history of cancer (P = 0.065), pack-years of smoking (P = 0.839), or the length of ex-smoking status (P = 0523). However, survivals were altered by other factors. The 5-year and 10-year survival rates tended to be lower as age increased with an exception for patients between 65 and 72 years of age. Both 5-year and 10-year survival rates decreased as tumor stage increased (P < 0.0001) with the most dramatic mortality noted in stage III and IV disease (see Fig. 3). Tumor size was examined closely to determine the relationship of tumor size irrespective of stage to survival. There were 661 patients with tumor size noted (436 males and 225 females). Analysis using Cox regression of tumors 0 to 1.0, 1.01 to 2.0, 2.01 to 3.0, 3.01 to 4.0, 4.01 to 5.0, and >5 cm showed increasing relative risk with tumor size regardless of stage, as well as decreasing 5-year survival of 48.6%, 45.9%, 26.6%, 27.0%, 14.4%, and 11.6%, respectively. The 5-year and 10-year survival rates were 48.6% and 39.2% for well-differentiated tumors, 34.6% and 10.8% for moderately differentiated tumors, and 21.4% and 10.9% for poorly differentiated tumors, respectively (P < 0.0001). In regard to tumor histology, the corresponding survival rates were 27.3% and 17.9% for adenocarcinomas, 21.2% and 6.6% for SCC, 11.6% and 5.7% for NSCLC-NOS, and 27.5% and 0% for adenosquamous tumors with a small number of patients (P < 0.0001), respectively. Complete resection of tumor resulted in a longer 5-year or 10-year survival (56.3% and 32.0%) compared with incomplete resection (29.4% and 15.2%) or no surgery (2.1% and 0.7%) with P < 0.0001 (Fig. 4).


Figure 3
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  		Figure 3. Kaplan-Meier survival curve for lung cancer based on stage (1990-2000, Walter Reed Army Medical Center).

 

Figure 4
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  		Figure 4. Kaplan-Meier survival curve for lung cancer based on surgical resection (1990-2000, Walter Reed Army Medical Center).

 
Using Cox regression analysis for independent variables, the HRs with respect to stage IA was 1.2 (95% CI, 0.9-1.8), 1.4 (95% CI, 0.9-2.1), 2.2 (95% CI, 1.6-3.2), and 4.6 (95% CI, 3.2-6.6) for stages IB, II, III, and IV, respectively. The HR estimates were 1.7 (95% CI, 1.3-2.4) and 3.0 (95% CI, 2.3-4.1) for incomplete and no surgical treatment relative to complete surgery, respectively. Table 4 that show the distribution of surgical treatment between African Americans and Caucasians. African Americans tended to more likely have no surgeries. However, "surgical treatment" was adjusted in the evaluation of racial differences. Ex-smoking status of 7 to 14 years was associated with deceased mortality (HR, 0.7; 95% CI, 0.2-0.9) compared with other durations (see Table 3). Tumors with bronchoalveolar carcinoma features had decreased risk of death (HR, 0.6; 95% CI, 0.4-1.0) compared with those without these features. After controlling for mutual effects of potential confounding in the Cox model, tumor stage, surgical treatment, length of ex-smoking status, and bronchoalveolar carcinoma features of cancer were significantly related to survival (see Table 3).


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  		Table 4. Distribution of surgical treatment between African Americans and Caucasians

 
Effect Modifications by Racial Background or Age
We also assessed to see whether the relationship between lung cancer survival and tumor features, surgical treatment, personal or family histories of cancer, and smoking was modified by racial background or gender. The only potential effect modification was noted with racial background and pack-years of smoking: increased pack-years of smoking might be related to increased lung cancer death in African Americans (Pinteraction by race = 0.047). Multivariant analysis using Cox regression shows male gender, stage III and IV disease, and completeness of resection to be the only significant factors in decreased survival with HR of 1.306 (95% CI, 1.019-1.675), 2.584 (95% CI, 1.568-4.260), 4.20 (95% CI, 2.505-7.401), and 4.060 (95% CI, 2.751-5.993), respectively. Bronchoalveolar carcinoma features and the length of the ex-smoking status seem to be markers of improved survival with HR of 0.345 (95% CI, 0.229-0.520; P < 0.0001), and ex-smoking status of >7 years with HR of 0.698 (95% CI, 0.493-0.989; P = 0.04). Race did not show an increased mortality risk.


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Our study showed that there were no racial disparities in lung cancer survival in a population with the same medical care access. However, gender was a factor related to the survival with a shorter survival for males. Other factors, including pathologic features of cancer, personal history of cancer, and surgical treatment, might also be influential on lung cancer survival.

Racial background and gender are found to represent a poor prognostic maker for disease behavior, suggesting variable access to medical care as likely reason for such survival disparity. Women with lung cancer had a better prognosis than men, perhaps because of the prevalence of adenocarcinomas (18), but African-American ethnic background patients are 2.5 times more likely to die from lung cancer compared with the Caucasian counterpart. It is very likely that poor outcome of lung cancer in former group is related to low socioeconomic status and low access to health care rather than tumor biology (19). Visbal et al. have examined >4,500 lung cancer patients with a male-to-female ratio of 3:2 and confirmed that men had an increased HR of 1.2 (95% CI, 1.11-1.3) compared with women controlling for multiple variables. The only other confounding factor in this study was the duration and amount of smoking in males compared with females (20). In a multiple prospective studies for advanced-stage lung cancer, the Cancer and Leukemia Group B examined ethnicity as a determinant factor for survival and reported that unadjusted 1-year survival was 22% in African Americans and 30% in non–African Americans. African-American patients in this analysis were more likely to be single, unemployed, and on Medicaid health care payer mode, suggesting that availability of medical care is an important factor as a survival determinant. Other studies have found discrepancy in lung cancer survival in relation to the availability of insurance coverage with a 3-year relative survival of 23% versus 13% for uninsured, concluding that disparities in cancer care and access to care were instrumental in this inequality. Furthermore, in a socialized medical system of Canada, Mackillop et al. linked statistically significant difference in lung cancer survival rates in poor-income communities (21). In South England, Gulliford et al. reviewed 32,818 patients from the Thames Cancer Registry and found that lack of access to specialty care was a key factor in mortality in lung cancer patients (22). The Eindhoven Cancer Registry review revealed a similar disparity in survival, which was attributed to access to specialized care (23). These studies have concluded that availability and access to health care may indeed be more important in determining the clinical outcome than previously thought.

The Walter Reed Health Care System has provided unlimited assess to care during the study period. All patients had unlimited access to similar treatment options when compared with other private and public health care systems. Our results suggest that medical care access can account for large proportion of ethnic differences in lung cancer survival. However, gender remained a predictive factor of lung cancer survival despite the same medical care access. In addition, other factors may influence lung cancer survival. A host of molecular markers have been associated with poor outcomes, including proliferating index (24), death-associated protein kinase promoter methylation, interleukin-10 protein expression (25), hypoxia-inducible factor-1{alpha} (26), EPGFR and HER-2 (27), and angiogenic peptides, such as vascular endothelial growth factor, epidermal growth factor, and microvessels density (28). In addition, recent studies have suggested that patients with family history of lung or other nondermatologic malignancies maybe at higher risk for developing lung tumors with more aggressive behavior (29-31). Smoking duration and histopathologic subtype have been reported to alter the clinical outcome. Tammemagi et al. examined >1,000 patients with lung cancer and concluded that significant predictors of morbidity included age, smoking, race/ethnicity, socioeconomic status, alcohol, and gender (32). Furthermore, data analysis of cigarette smoking habits were evaluated according to the Cox proportional hazards model using a total of 369 patients with stage I NSCLC. The results indicated that the cause of death and prevalence of tumor recurrence in lung cancer patients correlated with age and pack-years (33).

Other poor prognostic indicators include longer smoking status, larger primary tumor size, and higher clinical stage. Nordquist et al. also showed smoking status (HR, 1.325; 95% CI, 1.037-1.693) and stage (HR, 1.859; 95% CI, 1.685-2.051) to have a detrimental effect on survival of lung cancer patients (34). The 5-year survival of never smokers to current smokers was 28% and 22%, respectively (P = 0.0018). Furthermore, Okada et al. examined 1,000 consecutive stage I lung cancer patients and found that gender, age, and size of tumor were significant prognostic factors in survival. Male gender HR was 1.633 (95% CI, 1.008-1.022), and HR in larger tumor size was 1.022 (95% CI, 1.016-1.027; P < 0.0001). In addition, patients with elevated carcinoembryonic antigen and an incomplete resection have an even greater risk (HR, 1.968; 95% CI, 1.008-1.022; P = 0.0001) of mortality (35). In addition, studies suggesting that tumor sizes <2 cm in greatest dimension may be more significant than originally thought. Konaka et al. have reported no statistically significant survival advantage in tumors <1.0 versus 1.0 to 1.5 versus 1.5 to 2.0 at 100%, 84%, and 73.4% respectively. However, the study noted that lymph node metastasis was more common in tumors 1.5 to 2 cm in diameter (22% versus 14%) compared with tumors <1.5 cm in diameter (36). Additional studies reported that tumor size ≤1.5 cm had a better 5-year disease-free survival compared with lesions 1.6 to 3.0 cm in size (81.5% versus 78.6%; P = 0.03; ref. 37). A Cox regression analysis of this subgroup found tumor size (HR, 1.81; 95% CI, 1.01-3.47; P = 0.05) and poor tumor differentiation (HR, 1.87; 95% CI, 1.05-3.32; P = 0.03) to be significant factors in patient survival. Our data support the importance of tumor size regardless of the overall stage as an important factor in lung cancer survival. Our data show a difference with tumors ≤2.0 cm compared with 2 to 4 and >4 cm (53% versus 28% versus 17%). Tumor differentiation also was a significant predictor of survival in our patient population with well-differentiated tumors and tumors with bronchoalveolar carcinoma features having better survival. Furthermore, our results generally did not show the relation between these factors and lung cancer survival varied by racial background and gender.

Information on other treatments besides surgery were not available for data analysis, limiting our ability for additional analyses. These treatment factors can influence survival and may be related to the study factors, such as race, gender, and pathologic characteristics. Lack of controlling for these factors may be prone to potential residual confounding effects.

In conclusion, the overall survival of 22.4% was significantly better than the national data reported for the same period by Surveillance, Epidemiology, and End Results analysis. Male gender, completeness of resection, and stage III and IV disease are significant factors in diminishing survival of lung cancer patients. There was no evidence of racial bias in survival noted in our patient population. In fact, our overall survival data of African American was much better than the Surveillance, Epidemiology, and End Results data and was similar to the Caucasian patients. The effect of assess to care can be inferred but not confirmed by the improved overall survival of our patient population.


   Footnotes
 
Note: The views expressed in this article are the views of the authors and should not be construed as official or as reflecting the policies of the Department of the Army or Department of Defense.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 7/19/05; revised 10/ 3/05; accepted 11/ 1/05.


   References
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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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